Text Case Classification of Safety Production Accidents Based on Word2Vec Word Embedding and Clustering Model

doi:10.15888/j.cnki.csa.007744

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Home > Archive>Volume 30, Issue 1, 2021 >141-145. DOI:10.15888/j.cnki.csa.007744

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Text Case Classification of Safety Production Accidents Based on Word2Vec Word Embedding and Clustering Model
DOI:
                        10.15888/j.cnki.csa.007744
                    
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                        WU De-PingWU De-Ping
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221008, China;School of Network and Information Security, Jiangsu College of Safety Technology, Xuzhou 221011, China
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HUA GangHUA Gang
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221008, China
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Abstract:

The analysis of safety production accidents is of great significance to the improvement of emergency management ability. Based on the semantic analysis of safety production cases, Word2Vec embedding technology and clustering model are used, CBOW + negative sampling technology is used to realize word vector, and the data characteristics of safety production accident cases classification are combined, through semi-supervised learning based clustering model algorithm, according to the characteristics of the accident nature, an optimized initial clustering center algorithm is proposed, and K-means clustering algorithm is used to classify the text cases of safety accidents. The experimental results show that the proposed method can realize the classification of accident cases, and can be used for reference in the multi-dimensional analysis of accident.

Key words:Word2Vec word embedding;clustering;semi-supervised learning;safety production accidents;case classification

Reference

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吴德平,华钢.基于Word2Vec词嵌入和聚类模型的安全生产事故文本案例分类.计算机系统应用,2021,30(1):141-145

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Received:May 04,2020
Revised:June 10,2020
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Online: December 31,2020
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